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MaxEnt is useful here too

MaxEnt is useful here too. We last saw MaxEnt in the NLTK default tagger What is it doing?. Logistic regression. Very common machine learning technique Assign a positive/negative value to every feature Add up the values for features that are present The logit function tells

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MaxEnt is useful here too

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  1. MaxEnt is useful here too • We last saw MaxEnt in the NLTK default tagger • What is it doing?

  2. Logistic regression • Very common machine learning technique • Assign a positive/negative value to every feature • Add up the values for features that are present • The logit function tells you the probability • Learn the best values

  3. Example: movie reviews • funny = +1 • disappointed = -2 • seagal = -3

  4. High-level overview of MaxEnt • Now you have something more complicated than a yes/no question • You’re learning probability distributions instead of probabilities • The best probability distributions are the ones that are maximally uninformative about things you don’t know • Do things you’ve never observed happen 0% of the time? No, that’s assuming information you don’t have.

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